With the aim of obtaining a valid compression method for remote sensing and geographic information systems, and because comparisons among the different available techniques are not...
Compressive sampling offers a new paradigm for acquiring signals that are compressible with respect to an orthonormal basis. The major algorithmic challenge in compressive sampling...
A novel framework of compressed sensing, namely statistical compressed sensing (SCS), that aims at efficiently sampling a collection of signals that follow a statistical distribu...
We propose a compressive estimator of doubly selective channels within pulse-shaping multicarrier MIMO systems (including MIMOOFDM as a special case). The use of multichannel comp...
Leading compressed sensing (CS) methods require m = O (k log(n)) compressive samples to perfectly reconstruct a k-sparse signal x of size n using random projection matrices (e.g., ...